In [1]:
import stock_visualize as sv
import pandas as pd 

Welcome to use Wind Quant API for Python (WindPy)!

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IN NO CIRCUMSTANCE SHALL WIND BE RESPONSIBLE FOR ANY DAMAGES OR LOSSES CAUSED BY USING WIND QUANT API FOR Python.
In [2]:
case = sv.stock_visualize()
case.intro
case.testing()

换一个文件可以输出
In [3]:
from WindPy import w
w.start()
#w.isconnected()
data1 = w.wsd('600519.SH',['open','high','low','close','volume'],'-60D',usedf=True)

data1 = data1[1]
data1.columns = ['Open','High','Low','Close','Volume']
#print(data1.columns)
data1.index = pd.to_datetime(data1.index)
a = 0
case.simple_one_stock('600519.SH',data1)

打印成功
In [4]:
case.complicated_one_stock('600519.SH',data1)

打印成功
In [5]:
data2 = w.wsd(['000300.SH','000001.SH','300750.SZ'],'close','-60D',usedf=True)
data2 = data2[1]
for index,row in data2.iteritems():
    data2[index] /= data2[index][0] 

case.one_strategy_backtest(data2)

打印成功
In [6]:
data3 = w.wss(['600010.SH','000001.SZ','300750.SZ','600519.SH',\
        '600030.SH','000002.SZ','601012.SH','000333.SZ'],['pct_chg,sec_name'],"tradeDate=20211117;priceAdj=U;cycle=D",\
        usedf=True)
data3= data3[1]
data3
Out[6]:
PCT_CHG SEC_NAME
600010.SH 1.652893 包钢股份
000001.SZ -0.603732 平安银行
300750.SZ 1.774070 宁德时代
600519.SH -0.719027 贵州茅台
600030.SH 0.124948 中信证券
000002.SZ 1.143451 万科A
601012.SH 1.455879 隆基股份
000333.SZ -0.852468 美的集团
In [7]:
case.market_hearmap(data3)
In [8]:
data4 = {'name':['股票1','股票2','股票3'],'weight':[0.15,0.55,0.3]}
data4 = pd.DataFrame(data4)
data4
case.holding_weights(data4)